Additive random effects un lme
These are also called "crossed" random effects. lme can do them in a limited and complex way -- the syntax is given somewhere in one of the later chapters of the Pinheiro and Bates 2000 book [see https://stackoverflow.com/questions/36342072/how-to-get-two-random-effects-crossed-with-one-nested-in-the-other-in-nlme ] but it's much easier with lme4::lmer (y ~ 1 + (1|A) + (1|B)). Do you have a reason you have to stick with lme?
On 2018-09-19 01:33 PM, Mat?as Alejandro Castillo Moine wrote:
Hi everybody! Additive random effects in lme I?m working with lme() R function. I want to fit the following model y=u+A+B+e (where y is the response variable, u the general mean, A and B two categorical variables, and e the error term) but using only u as an fixed effect (so A and B must to be random effects but with additive response). How I can specify this model in lme function? At moment, I was found this manner: lme(y~1, random= ~1|A/B, data) But the problem is that, according to the documentation of nlme package, that sintaxis will to fit an nested model of B nested on A. In my case y are several biometrics variables of a crop, A are environments and B are genotypes. The term e will to include the interaction between A and B. Also, the error term is spatially correlated (I use the correlation argument for clean this effect). Thanks you for your help! Best regards, Mat?as A. Castillo Moine [[alternative HTML version deleted]]
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models